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Record W4409109742 · doi:10.1136/jmg-2024-110463

Clinical utility of genome sequencing in autism: illustrative examples from a genomic research study

2025· article· en· W4409109742 on OpenAlexafffund
Thanuja Selvanayagam, Ny Hoang, Ege Sarikaya, Jennifer Howe, Carolyn Russell, Alana Iaboni, Morgan Quirbach, Christian R. Marshall, Péter Szatmári, Evdokia Anagnostou, Jacob Vorstman, Dean M. Hartley, Stephen W. Scherer

Bibliographic record

VenueJournal of Medical Genetics · 2025
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsCentre for Addiction and Mental HealthHolland Bloorview Kids Rehabilitation HospitalUniversity of TorontoSickKids FoundationHospital for Sick ChildrenMcMaster University
FundersCanada Foundation for InnovationAutism SpeaksNational Institute of Mental HealthOntario Genomics InstituteOntario Brain InstituteCanadian Institutes of Health ResearchSick Kids FoundationGenome CanadaMcLaughlin Centre, University of Toronto
KeywordsMedical geneticsGenetic counselingAutismGenetic testingAutism spectrum disorderWhole genome sequencingPersonal genomicsGenomeGenomicsDNA sequencingGeneticsMedicineHuman geneticsComputational biologyBiologyPsychiatryGene

Abstract

fetched live from OpenAlex

BACKGROUND: Genetics is an important contributor to autism spectrum disorder (ASD). Clinical guidelines endorse genetic testing in the medical workup of ASD, particularly tests that use whole genome sequencing (WGS) technology. While the clinical utility of genetic testing in ASD is demonstrated, the breadth of impact of results can depend on the variant and/or gene being reported. METHODS: We reviewed research results returned to families enrolled in our ASD WGS study between 2012 and 2023. For significant results, we grouped the outcome of each genetic finding into three outcome categories: (1) genetic diagnosis, (2) counselling benefits and (3) support to family. RESULTS: Out of 202 families who received genome sequencing results, 100 had at least one clinically relevant finding related to ASD. With detailed examples, we show that all significant results led to a genetic diagnosis and counselling benefits. CONCLUSION: Our findings show the relevance of genome sequencing in ASD and provide illustrative examples of how the information can be used.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.258
GPT teacher head0.481
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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